1. Field of the Invention
The present invention generally relates to global navigation satellite system (GNSS) receivers and, more particularly, to a method and apparatus for generating long term orbit (LTO) models used by assisted GNSS receivers.
2. Description of the Related Art
Global Navigation Satellite System (GNSS) receivers require satellite navigation data in order to compute pseudo-ranges to the satellites of the GNSS system and, in turn, compute a position of the GNSS receiver. GNSS include such systems as GPS, GLONASS, and GALILEO. The satellite navigation data (i.e., commonly referred to as ephemeris) comprises both satellite orbits and clock models. Traditionally, GNSS receivers have decoded this navigation data from the broadcast signal transmitted by each satellite. More recently, Assisted-GNSS (or ‘A-GNSS’) receivers have received the broadcast data through an alternative communications channel, for example: a cellular telephone data connection. Yet more recently, the satellite navigation data has been modeled for long periods (i.e., days) in the future, and provided to A-GNSS receivers through a communications channel, or through some synchronization means such as through the docking port between a personal digital assistant (PDA) and a personal computer (PC), the PC connected to the Internet, and the data provided over the Internet.
Long Term Orbit and Clock models (collectively referred to as ‘LTO’ or sometimes referred to as extended ephemeris) provide satellite navigation data for long periods (days) in the future. One method of producing LTO measures the ranges to the satellites, using code phase measurements or carrier phase measurements, and fits these ranges to standard orbit models and clock models. An example of such a method is described in U.S. Pat. No. 6,542,820, which is hereby incorporated herein in its entirety. This patent also describes using ephemeris data (i.e., broadcast navigation data) as the input information from which LTO is computed. It has been found that the longer into the future the LTO is used, the less accurate it becomes. In particular, after several days, the median accuracy for the orbits and clock models may be quite accurate (i.e., within a few meters after several days), but the worst case accuracy may be large (i.e., tens of meters after several days). “Median” and “worst case” mean the median and worst case across the set of satellites. In particular, the worst case satellite clock model can be incorrect by much more than the orbit accuracy.
The official US government agency for disseminating orbit and clock data to the general public is the National Oceanic and Atmospheric Administration. The following information is from the USCG Navigation Center: ‘The U.S. Department of Transportation's Civil GPS Service has designated NOAA to be the federal agency responsible for providing accurate and timely. Global Positioning System (GPS) satellite ephemerides (“orbits”) to the general public.’ GPS satellite orbits can be found at http://www.nqs.noaa.gov/GPS/GPS.html.
Historic orbits are available (used for post-process positioning, for example, for surveying, measuring continental drifts, and the like) as well as limited future orbits. The types of data, latency and quoted accuracy of these orbits and clocks are listed in TABLE I.
TABLE IQuoted OrbitQuoted ClockDataLatencyaccuracyaccuracy“Precise Orbits”14 to 19 days<5 cm<0.1 ns (0.1 ns =0.03 m)“Rapid Orbits”1 day<5 cm0.1 ns (0.1 ns =0.03 m)“Ultra RapidUp to approx 18~10 cm ~5 ns (5 ns = 1.5 m)Orbits”hours in thefuture(in parentheses is shown the equivalent pseudo-range error in meters for the clock errors expressed in nanoseconds)
However, the worst case clock accuracy of the “Ultra Rapid Orbits” is many times worse than the quoted accuracy. This is immediately apparent when the clock values from the “Rapid Orbits” are compared to the clock predictions from the “Ultra Rapid Orbits”.
FIG. 1 depicts a graphical representation of a change in clock offset for both Rapid clock values and Ultra rapid clock predictions over the same period for all satellites. The pseudo-random number (PRN) code for each satellite is shown at the end of each of the plots. The Rapid clock values are made from measured data. The Ultra Rapid predictions are predictions up to one day in the future, made using data gathered in the past. The difference between measured values and predictions is not easily visible on the scale of FIG. 1, but is clearly in FIG. 2 which shows the Ultra Rapid predictions minus the Rapid clock values.
For many satellites the change in the clocks over one day is not very large (less than 100 m, or 0.33 microseconds), but for a few satellites (e.g., PRN 6 and 25 of FIG. 1) the change is large (on the order of kilometers, or several microseconds). This makes a significant difference in how difficult it is to predict these clocks, as shown in FIG. 2.
FIG. 2 depicts a graphical representation of the difference between the Ultra Rapid clock predictions and the Rapid clock values. According to the table of accuracy, the Ultra Rapid prediction is expected to agree with the Rapid clock value to within about 1.5 meters; and indeed this is true for many of the satellites, but for the worst-case satellites the error is an order of magnitude larger.
FIGS. 1 and 2 are a reflection of the state of the art: for most satellites, it is possible to predict the clock to within one or two meters for one day in the future, but for some satellites the prediction is worse than 10 meters one day in the future.
Therefore, there is a need in the art for a technique for determining future orbit and clock models with increased orbit and clock accuracy.